Machine Learning - PhD Internship
We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment.
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.
We are looking for talented Ph.D. students to have an internship in our fast moving team. You will have the opportunity to work on a very large scope of problems in search, personalization, recommendation, knowledge graph, pricing, etc. and on foundational machine learning infrastructures to empower all ML developments and applications.
ABOUT THE JOB
Based on your passion and background, you may choose to work in a few different areas:
- Query understanding - using cutting-edge NLP technologies to understand the intent of user queries.
- Generative AI initiatives - helping to build robust systems that directly support improvements to our NLP pipelines and the creation of new and magical user experiences.
- Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
- Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
- Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
- Efficient Retrieval System - Designing a scalable modern retrieval system to support ML systems in many business areas. Explore vector databases that treat embedding as a first-class citizen to support efficient retrieval at embedding space and leverage indices generated by large language models to provide better retrieval quality.
- Currently enrolled in a Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Operations Research, or a related technical field.
- Experience in one area of computer science (e.g., Machine Learning, Deep Learning, Natural Language Understanding, Computer Vision, Distributed System, Algorithmic Foundations of Optimization, Software Engineering, or similar).
- Experience with one or more general-purpose programming languages, including Python, Ruby, Go, C/C++, Java, or similar.
- Experience in machine learning applications
- Experience in engineering projects and understanding of the engineering development cycle.
- Strong software engineering background
- Experience contributing to research communities or efforts, including publishing papers in major conferences or journals.
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.
Offers may vary based on many factors, such as candidate experience and skills required for the role. Please read more about our benefits offerings here.
For US based candidates, the base pay ranges for a successful candidate are listed below.
Accommodations & Accessibility
At Instacart, we strive to create an accessible and inclusive experience for all candidates. If you need assistance submitting an application through our career site due to a disability, please submit an Accommodations Request Form and someone from our team will reach out soon to see how we may be able to assist.
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